Only in the Amazon do fish live where birds fly. Six months of the year, from
December to May, the Amazon River floods the surrounding rain forest, allowing
fish increased habitat during the rainy season.

Because of the difficulty of gaining access to the Amazon rain forest
interior, however, little is known about flooding extent. In addition to
obtaining a clear picture of Amazon flood patterns, scientists are interested in
determining the amount of water stored on floodplains during the wet season, and
the proportion of herbaceous versus woody vegetation that are important unknown
parameters in regional biogeochemical and hydrologic models.

Historically, obtaining any satellite data from the Amazon basin has been
as difficult as gaining physical access; radar images have provided the only
reliable source. Since the 1970s, the Brazilian government has acquired enough
radar data to issue a series of maps outlining the basin, constituting a basis
for many pioneering Amazon studies.

Recently, the Japanese, with help from the Brazilians and Americans, have
begun a new mapping effort using satellite remote sensing that offers several
advantages over earlier projects. Since mid-1995, a synthetic aperture radar
(SAR) aboard the Japanese Earth Resources Satellite-1 (JERS-1), has been
collecting data from the world's tropical forests. The first data acquisitions
of this project were of the Amazon rainforest during the low flood season of
1995.

It took 62 days to map the Amazon from coast to coast. Longer radar
wavelengths, provided by the SAR, penetrated both clouds and forest. The return
signal reveals the state of flooding beneath the forest canopy, simultaneously
allowing remote sensing scientists to distinguish between woody and herbaceous
plants.

Once collected, data were downloaded to the Alaska SAR Facility (ASF) for
processing into high-resolution images (12.5 meters), which were then sent to
the Jet Propulsion Lab (JPL) in California, where they were converted to
100-meter resolution images. The images were also converted to a graphical file
format and provided to the public via the World Wide Web. Finally, the images
were sent to the National Space Development Agency (NASDA) Earth Observation
Research Center in Japan, where individual images could be mosaicked to form
large, geocoded images of geographic regions.

With the high-resolution data, scientists are able to determine the extent
of flooding by comparing water extent for the dry and wet seasons. Knowledge of
flood extent and land cover distributions will offer new insight into the
Amazon's contribution to global methane emissions, said researcher Laura Hess,
of the University of California, Santa Barbara. "There are no current estimates
on the relative proportions of woody versus herbaceous vegetation in the Amazon
floodplain," said Hess. "This becomes important because the methane generation
for flood macrophyte (aquatic plant) beds is generally much higher than for flooded
forests."

"Floating meadows are very productive, floating masses of grass. The stems
elongate as the water rises and a canopy develops at the top of the water.
Grasses can reach several meters in length and float at the top of the water. As
water levels recede, the stems begin to decay. This causes a bubbling of methane
and high methane emissions," said Hess. "The proportion of floating meadows
increases as you go toward the mouth of the Amazon and the river channel
geomorphology changes."

In addition to enhancing biogeochemical models, the Amazon data sets will
be important for evaluating the health of fisheries that are essential to the
physical and economic welfare of the people inhabiting the Amazon basin, said
Hess.

Fish from the Amazon are a popular export to Asian countries, especially
Japan. They are also a key element in the diet of people living along the Amazon
River. Because of the high protein content of their diet, inhabitants along the
river are much less likely to be malnourished than rural people in regions
without fisheries, said Hess.

As the Amazon River rises, fish move through river channels into the
floodplains. Some fish, such as the tambaqui, are specially adapted to the
flooded forest environment. A keen sense of smell leads the tambaqui to fruit
which has fallen from the tree tops to the water. The tambaqui are genetically
adapted with powerful jaws and teeth that enable them to consume fruit. Not only
do they gain and store fat to last them through the dry season but in the
process they propagate the tree species by providing a dispersing mechanism for
the seeds.

Over the past 15 years, naturalist Michael Goulding has noticed a steady
decline in the size of many of the fish. This, together with increasing
agriculture, raises concern about over-fishing and habitat depletion, especially
in the lower Amazon where extensive agricultural production already exists and
continues to expand.

The satellite mapping has many applications. These include enhancing
scientific knowledge of river habitat, improving the existing geomorphologic
information base on the Amazon basin, and providing functional data sets for
geochemical modeling. The availability of this data set will offer scientists a
greater understanding of the role of floodplains in the basin's hydrology and
ecology, said Hess.

The international effort to map global rainforests is not limited to the
Amazon, nor is it limited to SAR data exclusively. Since radar can image day or
night, cloudy or clear, SAR data make it possible to study seasonal changes.
Mapping of floodplain vegetation and sediment concentrations of river channels
and lakes is also being carried out by Brazilian and American scientists using
Landsat Thematic Mapper data. Landsat data offer a much longer data record,
dating from the 1970s, offering researchers more detailed information on land
use changes. But the optical instrument can take years to acquire cloud-free
coverage over the entire basin.

Rather than abandoning Landsat data for new technology, scientists are
using SAR to continue the available record. The regions with the best images,
that is those with the least cloud cover, are archived in three blocks of time,
the early 1970s, mid 1980s, and early 1990s. The desired outcome of fine-tuning
the Landsat data is two-fold. The first outcome is to ensure that past data
collection efforts are not lost, the second is to facilitate global change
research. Data acquisition and processing are currently underway in Southeast
Asia and Africa, and archived Landsat data are being used to facilitate global
research.